Convolutional Generative Neural Networks (CGNNs) present as a powerful class of deep learning architectures for generating synthetic data. CGNNs integrate the strengths of convolutional neural networks well-known for their ability to learn spatial features with generative models, which are built to produce novel data instances. This survey provides